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Lookup NU author(s): Professor Boguslaw ObaraORCiD
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Many biomedical applications require the detection of branching structures in images. While several algorithms have been proposed for (semi-)automatic extraction of these structures, branching points usually need specific treatment. We propose a vector field-based approach to identify branching points in images. A vector field is calculated using a novel contrast-independent tensor representation based on local phase. Non-curvilinear structures, including junctions and end points, are detected using directional statistics of the principal orientation as defined by the tensor. Results on synthetic and real biomedical images show the robustness of the algorithm against changes in contrast, and its ability to detect junctions in highly complex images. © 2012 SPIE.
Author(s): Obara B, Fricker M, Grau V
Editor(s): David R. Haynor, Sébastien Ourselin
Publication type: Conference Proceedings (inc. Abstract)
Publication status: Published
Conference Name: Medical Imaging 2012: Image Processing
Year of Conference: 2012
Online publication date: 14/02/2012
Publisher: SPIE
URL: https://doi.org/10.1117/12.910575
DOI: 10.1117/12.910575
Library holdings: Search Newcastle University Library for this item
Series Title: SPIE Proceedings
ISBN: 9780819489630